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he accompanying data file contains 35 observations for an ice cream truck driver's daily income (Income in $), number f hours on the road (Hours),

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he accompanying data file contains 35 observations for an ice cream truck driver's daily income (Income in \$), number f hours on the road (Hours), whether it was a particularly hot day (Hot =1 if the high temperature was above 85F,0, therwise), and whether it was a Holiday (Holiday =1,0 otherwise). Consider two models where Model 1 predicts come on the basis of Hours, Hot, and Holiday and Model 2 also includes the interaction between Hot and Holiday. lick here for the Excel Data File -1. Use the holdout method to compare the predictability of the models using the first 24 observations for training and he remaining 11 observations for validation. Report the estimates of Models 1 and 2 derived from the training set. lote: Negative values should be indicated by a minus sign. Round your answers to 2 decimal places. -2. Calculate the RMSE of the two models in the validation set. Jote: Do not round intermediate calculations and round your final -3. Which model is better for making predictions? \begin{tabular}{|l|l|l|l|} \hline Income & Hours & Hot & Holiday \\ \hline 196 & 5 & 1 & 0 \\ \hline 282 & 8 & 0 & 0 \\ \hline 318 & 6 & 1 & 0 \\ \hline 232 & 5 & 1 & 0 \\ \hline 276 & 8 & 0 & 0 \\ \hline 312 & 8 & 0 & 1 \\ \hline 193 & 5 & 0 & 1 \\ \hline 110 & 4 & 0 & 0 \\ \hline 321 & 8 & 1 & 0 \\ \hline 283 & 8 & 0 & 0 \\ \hline 325 & 8 & 1 & 0 \\ \hline 247 & 7 & 5 & 1 \\ \hline 398 & 8 & 1 & 1 \\ \hline 448 & 8 & 1 & 1 \\ \hline 214 & 4 & 0 & 0 \\ \hline 235 & 8 & 0 & 0 \\ \hline 238 & 8 & 0 & 0 \\ \hline 148 & 3 & 1 & 0 \\ \hline 284 & 8 & 0 & 1 \\ \hline 449 & 8 & 1 & 1 \\ \hline 332 & 8 & 1 & 1 \\ \hline 247 & 8 & 0 & 0 \\ \hline 363 & 7 & 1 & 0 \\ \hline 393 & 7 & 1 & 1 \\ \hline 284 & 8 & 0 & 0 \\ \hline 228 & 8 & 0 & 0 \\ \hline 355 & 6 & 1 & 1 \\ \hline 248 & 7 & 0 & 1 \\ \hline 291 & 8 & 1 & 0 \\ \hline 255 & 5 & 1 & 0 \\ \hline 239 & 6 & 0 & 0 \\ \hline 181 & 6 & 0 & 0 \\ \hline 222 & 7 & 0 & 0 \\ \hline 170 & 5 & 0 & 1 \\ \hline 374 & 6 & 1 & 1 \\ \hline \end{tabular} he accompanying data file contains 35 observations for an ice cream truck driver's daily income (Income in \$), number f hours on the road (Hours), whether it was a particularly hot day (Hot =1 if the high temperature was above 85F,0, therwise), and whether it was a Holiday (Holiday =1,0 otherwise). Consider two models where Model 1 predicts come on the basis of Hours, Hot, and Holiday and Model 2 also includes the interaction between Hot and Holiday. lick here for the Excel Data File -1. Use the holdout method to compare the predictability of the models using the first 24 observations for training and he remaining 11 observations for validation. Report the estimates of Models 1 and 2 derived from the training set. lote: Negative values should be indicated by a minus sign. Round your answers to 2 decimal places. -2. Calculate the RMSE of the two models in the validation set. Jote: Do not round intermediate calculations and round your final -3. Which model is better for making predictions? \begin{tabular}{|l|l|l|l|} \hline Income & Hours & Hot & Holiday \\ \hline 196 & 5 & 1 & 0 \\ \hline 282 & 8 & 0 & 0 \\ \hline 318 & 6 & 1 & 0 \\ \hline 232 & 5 & 1 & 0 \\ \hline 276 & 8 & 0 & 0 \\ \hline 312 & 8 & 0 & 1 \\ \hline 193 & 5 & 0 & 1 \\ \hline 110 & 4 & 0 & 0 \\ \hline 321 & 8 & 1 & 0 \\ \hline 283 & 8 & 0 & 0 \\ \hline 325 & 8 & 1 & 0 \\ \hline 247 & 7 & 5 & 1 \\ \hline 398 & 8 & 1 & 1 \\ \hline 448 & 8 & 1 & 1 \\ \hline 214 & 4 & 0 & 0 \\ \hline 235 & 8 & 0 & 0 \\ \hline 238 & 8 & 0 & 0 \\ \hline 148 & 3 & 1 & 0 \\ \hline 284 & 8 & 0 & 1 \\ \hline 449 & 8 & 1 & 1 \\ \hline 332 & 8 & 1 & 1 \\ \hline 247 & 8 & 0 & 0 \\ \hline 363 & 7 & 1 & 0 \\ \hline 393 & 7 & 1 & 1 \\ \hline 284 & 8 & 0 & 0 \\ \hline 228 & 8 & 0 & 0 \\ \hline 355 & 6 & 1 & 1 \\ \hline 248 & 7 & 0 & 1 \\ \hline 291 & 8 & 1 & 0 \\ \hline 255 & 5 & 1 & 0 \\ \hline 239 & 6 & 0 & 0 \\ \hline 181 & 6 & 0 & 0 \\ \hline 222 & 7 & 0 & 0 \\ \hline 170 & 5 & 0 & 1 \\ \hline 374 & 6 & 1 & 1 \\ \hline \end{tabular}

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